Abstract
Precision farming is an approach that provides the capacity to manage the yield based on spacialized information. Yield map is an important information as it describes the answer of the crop to the inputs and soil conditions. Due to the automation of data collection some errors may occur and the elimination of those errors from the data represents information quality. This work proposes the development of a filtering routine of raw data to eliminate errors. The first step is the analysis and characterization of the errors present on data from six different commercial yield monitors. A methodology was developed to identify the running direction of the machine, allowing the estimation of the filling time error. Yield outlier limits were established and values over and under the limits were found in the data. Based on the characteristics of each error, a filtering routine was developed. The routine has seven steps, each one acting over different errors. The filtering process improved the semivariance analysis and the final quality of yield maps.
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Claims 4
Claim · model-written summary
A methodology identified machine running direction to estimate filling time error.
- Outcome
- estimation of the filling time errore0
Not reportedTaxonComparatorValue
Verbatim
e0“A methodology was developed to identify the running direction of the machine, allowing the estimation of the filling time error.”
Claim · model-written summary
Yield outlier limits identified values above and below the limits.
- Outcome
- values over and under the limitse0
Not reportedTaxonComparatorValue
Verbatim
e0“Yield outlier limits were established and values over and under the limits were found in the data.”
Claim · model-written summary
The filtering routine comprised seven steps targeting different errors.
Not reportedTaxon
Verbatim
e0“The routine has seven steps, each one acting over different errors.”
Claim · model-written summary
Filtering improved semivariance analysis and final yield-map quality.
Not reportedTaxonComparator
Verbatim
e0“The filtering process improved the semivariance analysis and the final quality of yield maps.”